EFFECT OF FOOT REFLEXOLOGY VERSUS ACUPRESSURE ON SLEEP DISTURBANCES AND HOT FLASHES IN POSTMENOPAUSAL WOMEN
Bibliographic record
Abstract
Objective: The aim of the study was to find out the impact of foot reflexology versus acupressure on sleep disturbances and hot flashes in postmenopausal women. Methods: Fifty-four postmenopausal women suffering from postmenopausal sleep disturbances and hot flashes were randomly allocated into two equal groups: Group A, (n=27) treated by foot reflexology for fifteen minutes, 3 sessions per week for six weeks, and Group B, (n=27) treated by acupressure for twenty-one minutes, 3 sessions per week for six weeks. Sleep quality was evaluated by Pittsburgh Sleep Quality Index, and hot flashes severity by Hot Flashes Questionnaire before and after six weeks of the treatment protocol. Results: There were statistically significant improvements (p < 0.05) in pittsburgh sleep quality index score, and hot flashes questionnaire score in both groups after treatment compared with baseline. When comparing both groups, post-treatment results revealed significant improvements in pittsburgh sleep quality index score, and hot flashes questionnaire score (p < 0.001) in favor of group (B). Conclusion: Both acupressure, as well as foot reflexology were effective therapeutic modality for management of postmenopausal women with superior to acupressure for gained improvements in sleep quality, and severity of hot flashes among postmenopausal women.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".